My Citizen Analyst Tweetchat Summary

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Yesterday I had the opportunity to be a special guest for IBM Watson Analytics’ Citizen Analyst Tweetchat, answering 8 interesting questions about the role and power of the Citizen Analyst. I’ve expanded my original 140 character answers below.

What is a Citizen Analyst?

Like a citizen journalist, a Citizen Analyst is a person with analytical skills applying their talents to their passions. Citizen Analysts examine, fact check, and showcase good and bad uses of data in the public sphere.

A great example of a Citizen Analyst is my friend and colleague Tom Webster who often calls out terrible data like this:

Citizen Analysts (or really, anyone with a modicum of mathematical sense) answer the call to battle when bad analysis appears.

What does it take to be a Citizen Analyst?

A series of personality traits:

Curiosity.
Honesty.
Boldness.
Insight.
Humility.
Persistence.
Dedication.
Fearlessness.
Numeracy.

A while back I wrote a piece for SHIFT Communications on what it means to be a Citizen Analyst, the Citizen Analyst Manifesto.

Who can be a Citizen Analyst?

Anyone. I often use this formula as shorthand:

Attitude + Aptitude = Altitude

It’s a way of saying that if you have the motivation and the skills, you choose how high you want to fly, how successful you want to be, from a marketing technologist to a Citizen Analyst.

What’s the most important thing a Citizen Analyst should know?

Prospective Citizen Analysts need to beware of two biases. First, know what the Dunning-Kruger effect is. Dunning-Kruger – a belief by low-ability individuals in their illusory superiority – is a significant cognitive bias, and only humility protects you against it, which is why humility is one of the core values of the Citizen Analyst.

The second is expectation bias. Don’t start analysis with a pre-ordained conclusion in mind. That’s the 100% wrong way to do it. Passion should inspire and motivate you, but not dictate the narrative or objectivity of your data. This is especially problematic for causes and the political realm, where you have an axe to grind about a candidate, party, or position and you cherry-pick data that supports your position. Doing so destroys any credibility you might have had.

What advice would you give to a new Citizen Analyst?

Start small.
Use the tools you have.
Ask lots of questions starting with "What if…"

Fellow IBM Predictioneer Randy Krum cautions us to remember that discovery and communication of data are different mindsets and different outputs. They are not one and the same and should not be treated the same way.

To get started, I recommend reading Edward Tufte’s Visualization of Quantitative Information. It’s an amazing work and thought-starter.

Then read/take courses on statistics 101 and especially forms of statistical bias.

Which tools would you recommend a Citizen Analyst use?

Data quality > tools. The best frying pan in the world can’t make rotten eggs taste any better. Be sure your data is pristine before worrying about which tools.

That said, I’m a fan of IBM Watson Analytics, of course. A good spreadsheet is essential. A good text editor is also essential. Be familiar with many of the big database packages out there, from MySQL to BigQuery. Understand the uses of Python and R. Gain familiarity with big data tools like Rapidminer, Alteryx, and KNIME.

What types of things might a new Citizen Analyst review?

Fact-checking politicians. The 2016 election is rife with misuse of objective data. Politicians are bad; news outlets are worse. The amount of misinformation and incorrect analysis is stunning, regardless of your politician orientation.
Citizen Analysts can question business & marketing claims, especially about high-profile cases. We’ve seen many stories recently about medical device manufacturers escalating price increases like crazy; a Citizen Analyst is uniquely positioned to invest time and effort to determine whether such price increases are aligned with historical data.
Fact-checking governmental claims, especially from governments with spurious data. For example, in the Syrian civil war, casualty claims are wildly different based on who you listen to. Citizen Analysts can ingest multiple data sources, weight them, and develop an understanding of what’s really happening.

Why do we need Citizen Analysts if we have BI folks?

Citizen Analysts examine data others might not find profitable or the best use of time.

Citizen Analysts bring a different perspective to the same data, different points of view.

Citizen Analysts bring datasets that BI pros may not know about or have access to. The number of BI professionals I know who haven’t heard of Kaggle or Data.gov is staggering.

Catch me at IBM World of Watson!

I’ll be presenting in more depth on the topic of the Citizen Analyst at IBM’s World of Watson conference in late October. I hope to see you there!